Abstract
Steady and rapid development of smart grid provides necessary technical support for the intelligent control of electric vehicle (EV). In this paper the private EV is taken as the research subject, an EV direct intelligent management system considering various realistic factors is proposed, charging load profile is established by Monte Carlo sampling method. Then the 0-1 mixed integer programming optimization model is formulated to minimize the users’ electricity cost and variance of system load. The EV night-charging in some district is researched as an example and the control effectiveness of different control strategies is analyzed. The results show that the two control strategies are both conducive to flattening the load curve, and the strategies improve the system operation efficiency and security and reduce the user's electricity cost.
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